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#MIT Schwarzman College of Computing

  • At MIT, a continued commitment to understanding intelligence

    16 Jan
  • Generative AI tool helps 3D print personal items that sustain daily use

    16 Jan
  • 3 Questions: How AI could optimize the power grid

    16 Jan
  • MIT scientists investigate memorization risk in the age of clinical AI

    16 Jan
  • MIT in the media: 2025 in review

    16 Jan
  • Guided learning lets “untrainable” neural networks realize their potential

    16 Jan
  • A new way to increase the capabilities of large language models

    16 Jan
  • 3 Questions: Using computation to study the world’s best single-celled chemists

    16 Jan
  • Enabling small language models to solve complex reasoning tasks

    16 Jan
  • New MIT program to train military leaders for the AI age

    16 Jan
  • New method improves the reliability of statistical estimations

    16 Jan
  • New materials could boost the energy efficiency of microelectronics

    16 Jan
  • MIT affiliates named 2025 Schmidt Sciences AI2050 Fellows

    16 Jan
  • MIT researchers “speak objects into existence” using AI and robotics

    16 Jan
  • A smarter way for large language models to think about hard problems

    16 Jan
  • MIT engineers design an aerial microrobot that can fly as fast as a bumblebee

    16 Jan
  • New control system teaches soft robots the art of staying safe

    16 Jan
  • MIT Sea Grant students explore the intersection of technology and offshore aquaculture in Norway

    16 Jan
  • Researchers discover a shortcoming that makes LLMs less reliable

    16 Jan
  • MIT scientists debut a generative AI model that could create molecules addressing hard-to-treat diseases

    16 Jan
  • Understanding the nuances of human-like intelligence

    16 Jan
  • Charting the future of AI, from safer answers to faster thinking

    16 Jan
  • MIT researchers propose a new model for legible, modular software

    16 Jan
  • Teaching robots to map large environments

    16 Jan
  • 3 Questions: How AI is helping us monitor and support vulnerable ecosystems

    16 Jan
  • A faster problem-solving tool that guarantees feasibility

    16 Jan
  • Five with MIT ties elected to National Academy of Medicine for 2025

    16 Jan
  • Creating AI that matters

    16 Jan
  • New software designs eco-friendly clothing that can reassemble into new items

    16 Jan
  • Method teaches generative AI models to locate personalized objects

    16 Jan
  • Blending neuroscience, AI, and music to create mental health innovations

    16 Jan
  • MIT Schwarzman College of Computing and MBZUAI launch international collaboration to shape the future of AI

    16 Jan
  • Using generative AI to diversify virtual training grounds for robots

    16 Jan
  • Fighting for the health of the planet with AI

    16 Jan
  • New prediction model could improve the reliability of fusion power plants

    16 Jan
  • AI maps how a new antibiotic targets gut bacteria

    16 Jan
  • Responding to the climate impact of generative AI

    16 Jan
  • New AI system could accelerate clinical research

    16 Jan
  • What does the future hold for generative AI?

    16 Jan
  • How to build AI scaling laws for efficient LLM training and budget maximization

    16 Jan
  • Machine-learning tool gives doctors a more detailed 3D picture of fetal health

    16 Jan
  • DoE selects MIT to establish a Center for the Exascale Simulation of Coupled High-Enthalpy Fluid–Solid Interactions

    16 Jan
  • A greener way to 3D print stronger stuff

    16 Jan
  • A new generative AI approach to predicting chemical reactions

    16 Jan
  • 3 Questions: The pros and cons of synthetic data in AI

    16 Jan
  • 3 Questions: On biology and medicine’s “data revolution”

    16 Jan
  • MIT researchers develop AI tool to improve flu vaccine strain selection

    16 Jan
  • Simpler models can outperform deep learning at climate prediction

    16 Jan
  • Can large language models figure out the real world?

    16 Jan
  • A new way to test how well AI systems classify text

    16 Jan
  • Eco-driving measures could significantly reduce vehicle emissions

    16 Jan
  • MIT tool visualizes and edits “physically impossible” objects

    16 Jan
  • New algorithms enable efficient machine learning with symmetric data

    16 Jan
  • Robot, know thyself: New vision-based system teaches machines to understand their bodies

    16 Jan
  • A new way to edit or generate images

    16 Jan
  • The unique, mathematical shortcuts language models use to predict dynamic scenarios

    16 Jan
  • Can AI really code? Study maps the roadblocks to autonomous software engineering

    16 Jan
  • How to more efficiently study complex treatment interactions

    16 Jan
  • Changing the conversation in health care

    16 Jan
  • AI shapes autonomous underwater “gliders”

    16 Jan
  • Study could lead to LLMs that are better at complex reasoning

    16 Jan
  • Using generative AI to help robots jump higher and land safely

    16 Jan
  • LLMs factor in unrelated information when recommending medical treatments

    16 Jan
  • Researchers present bold ideas for AI at MIT Generative AI Impact Consortium kickoff event

    16 Jan
  • Unpacking the bias of large language models

    16 Jan
  • A sounding board for strengthening the student experience

    16 Jan
  • Bringing meaning into technology deployment

    16 Jan
  • Photonic processor could streamline 6G wireless signal processing

    16 Jan
  • Inroads to personalized AI trip planning

    16 Jan
  • Melding data, systems, and society

    16 Jan
  • AI-enabled control system helps autonomous drones stay on target in uncertain environments

    16 Jan
  • Envisioning a future where health care tech leaves some behind

    16 Jan
  • Teaching AI models what they don’t know

    16 Jan
  • Teaching AI models the broad strokes to sketch more like humans do

    16 Jan
  • An anomaly detection framework anyone can use

    16 Jan
  • Building networks of data science talent

    16 Jan
  • AI learns how vision and sound are connected, without human intervention

    16 Jan
  • Learning how to predict rare kinds of failures

    16 Jan
  • The sweet taste of a new idea

    16 Jan
  • With AI, researchers predict the location of virtually any protein within a human cell

    16 Jan
  • Study shows vision-language models can’t handle queries with negation words

    16 Jan
  • MIT Department of Economics to launch James M. and Cathleen D. Stone Center on Inequality and Shaping the Future of Work

    16 Jan
  • Hybrid AI model crafts smooth, high-quality videos in seconds

    16 Jan
  • New tool evaluates progress in reinforcement learning

    16 Jan
  • Novel AI model inspired by neural dynamics from the brain

    16 Jan
  • Making AI models more trustworthy for high-stakes settings

    16 Jan
  • The MIT-Portugal Program enters Phase 4

    16 Jan
  • Merging design and computer science in creative ways

    16 Jan
  • Designing a new way to optimize complex coordinated systems

    16 Jan
  • “Periodic table of machine learning” could fuel AI discovery

    16 Jan
  • 3D modeling you can feel

    16 Jan
  • MIT’s McGovern Institute is shaping brain science and improving human lives on a global scale

    16 Jan
  • Making AI-generated code more accurate in any language

    16 Jan
  • A faster way to solve complex planning problems

    16 Jan
  • Training LLMs to self-detoxify their language

    16 Jan
  • New method efficiently safeguards sensitive AI training data

    16 Jan
  • Could LLMs help design our next medicines and materials?

    16 Jan
  • New method assesses and improves the reliability of radiologists’ diagnostic reports

    16 Jan
  • Researchers teach LLMs to solve complex planning challenges

    16 Jan
  • For this computer scientist, MIT Open Learning was the start of a life-changing journey

    16 Jan

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